Classification of Electrical Tree Growth Stages in XLPE Cable Insulation using CNN and Pre-trained CNNs

Abstract

Electrical treeing, a significant degradation process in XLPE insulated cables, presents a substantial risk as it gradually weakens the insulation, ultimately leading to failure. Thus, understanding and identifying various stages of electrical tree growth is essential for implementing effective condition monitoring strategies. This study focuses on classification of electrical tree images into Inception, Propagation, and Breakdown stages utilizing state of the art CNN and pre-trained CNNs, including InceptionNet, ResNet, and EfficientNet. The impact of different optimizers such as Adam, RMSprop, and SGD on the performance of these approaches was evaluated in this study. The results showcased the effectiveness of the EfficientNet model with the RMSprop optimizer, achieving an accuracy of 98.78%.